去年归国的徐梦迪，成了清华姚班班主任

TL;DR - Robotics researcher Mengdi Xu, who returned from Stanford to Tsinghua University in 2025, has become a faculty adviser for the elite Yao Class. Her work argues that general-purpose robots need rapid adaptation, reusable skills, and reliable instruction-following—not scaling alone.

• Xu’s CMU award-winning dissertation explored few-shot task adaptation, transferable robot skills, and using LLM knowledge for physical problem-solving.
• Prompting Decision Transformer adapts policies to unseen tasks from short demonstration trajectories without additional parameter fine-tuning.
• RoboTool analyzes physical constraints, selects tools, plans actions, and generates executable code, enabling robots to devise unconventional solutions.
• Her Tsinghua research targets robots that are scalable, adaptable, and reliable, spanning robot learning, human-robot interaction, and AI safety.